# Lab Session 5 - 7 July 2023: Regression Models

https://scikit-learn.org/stable/tutorial/machine_learning_map/index.html

The lecture slides is here: https://liveutm-my.sharepoint.com/:p:/g/personal/azizulazizan_live_utm_my/Ed6aM3zU3xZKstbo8AseSCQBJ1mMtoTnPy89wrxuX1DMQw?e=WqhOXP

Colab code Chapter 4: https://github.com/ageron/handson-ml2/blob/master/04_training_linear_models.ipynb

Please give the thetha0 and thetha1 for

Example:
1. Normal Equation = [4.21509616],[2.77011339]

M Nuaimi:
1. Normal Equation = [4.21509616], [2.77011339]
2. Least Square Fit =[4.21509616], [2.77011339]
3. Batch GD =[4.21509616], [2.77011339]
4. Stocastic GD =[4.21076011], [2.74856079]
5. Mini-batch GD =[4.25214635], [2.7896408 ]

Danyar:
1. Normal Equation = ([[4.21509616],
[2.77011339]])
2. Least Square Fit = [[4.21509616],
[2.77011339]]
3. Batch GD = ([[4.21509616],
[2.77011339]])
4. Stocastic GD = ([[4.21076011],
[2.74856079]])
5. Mini-batch GD = [[4.25214635],
[2.7896408 ]]

Moric:
1. Normal Equation = [4.21509616],[2.77011339]
2. Least Square Fit =[4.21509616],[2.77011339]
3. Batch GD =[4.21509616],[2.77011339]
4. Stocastic GD =[4.21076011],[2.74856079]
5. Mini-batch GD =[4.25214635],[2.7896408 ]

M Umar:
1. Normal Equation = array([[4.21509616],
[2.77011339]])
2. Least Square Fit = array([[4.21509616],
[2.77011339]])
3. Batch GD = array([[4.21509616],
[2.77011339]])
4. Stocastic GD = array([[4.21076011],
[2.74856079]])
5. Mini-batch GD = array([[3.96299242],
[2.96388645]])

Azlan:
1. Normal Equation = [4.21509616],[2.77011339]
2. Least Square Fit =[4.21509616],[2.77011339]
3. Batch GD =[4.21509616],[2.77011339]
4. Stocastic GD =[4.21076011],[2.74856079]
5. Mini-batch GD = [4.25214635],[2.7896408 ]